Name
Abstract | ||
|---|---|---|
Detecting surface defects of alumina substrate by using computer technique will enhance productivity in industrial manufacture. Edge detection of image is the commonly used technique for the detection of surface defects. However, it is difficult to automatically detect the surface defects of the alumina substrate since the noise and the multiple kinds of defects may exist in a substrate. In this paper, we designed an edge detection algorithm based on Canny detector aiming to automatically detect the surface defects of alumina substrate. Our algorithm can adaptively smooth image as well as adaptively determine the low threshold and high threshold. Experiments show that our algorithm can effectively and automatically detect several kinds of surface defects in the alumina substrate. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-030-00021-9_44 | CLOUD COMPUTING AND SECURITY, PT VI |
Keywords | Field | DocType |
Alumina ceramic, Surface defect, Defect detection, Canny algorithm, Lifting wavelet, Multilevel Otsu algorithm | Substrate (chemistry),Computer vision,Computer science,Edge detection,Real-time computing,Artificial intelligence,Detector | Conference |
Volume | ISSN | Citations |
11068 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 8 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chaorong Li | 1 | 47 | 5.47 |
| Liangwei Chen | 2 | 0 | 1.01 |
| Lihong Zhu | 3 | 20 | 2.35 |
| Yu Xue | 4 | 871 | 60.17 |